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Hadoop-ML: An Infrastructure for the Rapid Implementation of Parallel Reusable Analytics

Hadoop-ML: An Infrastructure for the Rapid Implementation of Parallel Reusable Analytics

This video was recorded at NIPS Workshops, Whistler 2009. Hadoop is an open-source implementation of Google's Map-Reduce programming model. Over the past few years, it has evolved into a popular platform for parallelization in industry and academia. Furthermore, trends suggest that Hadoop will likely be the analytics platform of choice on forthcoming Cloud-based systems. Unfortunately, implementing parallel machine learning/data mining (ML/DM) algorithms on Hadoop is complex and time consuming. To address this challenge, we present Hadoop-ML, an infrastructure to facilitate the implementation of parallel ML/DM algorithms on Hadoop. Hadoop-ML has been designed to allow for the specification of both task-parallel and data-parallel ML/DM algorithms. Furthermore, it supports the composition of... Show More

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